IoT is scalable and has flexible evolution options, making it an excellent starting point towards digital transformation.
Fremont, CA: IoT-enabled condition monitoring is a great place to start businesses looking to implement IoT in manufacturing because it provides instant value and implementation iteratively.
Condition tracking, made possible by the Internet of Things, serves as a source of real-time data mainly on the condition of industrial machinery and its operating environment.IoT is scalable and has flexible evolution options, making it an excellent starting point towards digital transformation.
Condition monitoring based on IoT
IoT in manufacturing: Iteration drives value
IoT-driven condition monitoring uses data to track the present condition of industrial machinery or identify combinations of environmental and operational parameters that may cause product quality to deteriorate or lead to equipment failure.
The capabilities of IoT-enabled condition monitoring, on the other hand, are far broader. The solution achieves advanced capabilities, such as more profound control and analytics, when implemented correctly and can be useful as a catalyst for many other IoT initiatives. However, this will result in changes at any step of the implementation process.
When an IoT project begins with the fundamental architecture, it yields a quick return on investment. It prevents overspending—extending it to improve the solution's versatility and build further use cases once it's appropriately developed.
Building the basics: Finding the pattern
The specifics of implementation can vary depending on the type of equipment used and the manufacturer since each asset type has its own particular regular behavioral pattern. IoT in manufacturing, on the other hand, has four essential components:
Cloud and field gateways are often helpful to securely link industrial machinery to cloud applications, ensuring uninterrupted data flow.
Field gateways process sensor data before being sent to the cloud. The filtering and aggregation of messages are part of this field pre-processing. By discarding intermediate data points, field gateways achieve more effective data transmission.
Ambient parameters (such as humidity and temperature) and equipment data are often valuable for IoT-driven condition monitoring. Sensors directly attached to the computer, a PLC, or a SCADA device can provide this information.
3. Big data warehouse
Meanwhile, a big data warehouse stores sensor data and critical contextual data such as operating parameters, including equipment maintenance records gathered from ERP and many other systems.
4. Data lake
The IoT-driven condition monitoring solution can then approach the next level with analytics and user applications once the basics are in place.
Ramping up: Analytics and user applications
The IoT-driven condition monitoring solution can be taken to the next level with analytics and user applications if the basics are in place.
Data analytics tools are helpful to turn raw sensor data into equipment condition insights by running sensor readings via analytics algorithms. User apps will then imagine and convey the results to users.
User apps enable users or the monitoring solution to communicate in both directions. User apps present data analytics insights in equipment health dashboards, graphs, and maps, among other things.